This proposal, from a new investigator, aims to determine whether epigenetic modification of DNA differs between depressed and control subjects, and whether relevant epigenetic marks are influenced by genetic variation and by heavy alcohol and/or cannabis use. This project will take advantage of an existing close collaboration, between groups within psychiatry and genetic medicine, that brings together 2 outstanding resources: a very large and rigorously assessed sample of familial major depression, from the Genetics of Recurrent Early Onset Depression (GENRED) study, co-led by Dr. J. Raymond DePaulo, Jr., and the state of-the-art methods for the study of epigenetic modification available through the Center for the Epigenetics of Common Disease, led by Dr. Andrew Feinberg. In this proposal, DNA methylation in gene promoters, a key epigenetic mechanism that can influence gene expression, will be compared between depressed and control subjects. Similarly, unequal allelic expression, a potential indicator of epigenetic variation, will be assessed in these subjects. The former assay will use whole blood DNA, while the latter will test cultured lymphocytes. For both assays, post-mortem brain tissue will also be employed as part of an initial screen for variability. Genes that are positive for variability in both blood-derived and brain tissues will be tested in 297 GENRED cases and 297 controls. The genes to be analyzed include 14 functional candidates and 43 positional candidates, the latter being those under a 15q25-26 linkage peak recently reported in the GENRED sample. Bioinformatic analysis will assess potentially methylation-sensitive transcription factor binding sites and glucocortocoid modulatory elements in the promoter regions of these genes, to ensure that these functionally relevant CpG dinucleotide-containing sequences are prioritized for study. Where epigenetic differences are found in depressed subjects, genotyping within implicated genes will be performed to test for genotype epigenotype association, and existing genome-wide microsatellite data will be used for linkage with epigenotype as an endophenotype. Alcohol and cannabis abuse and dependence diagnoses will be tested for their association with epigenotypes. Interactions among variables will also be explored using regression models. Results from the novel studies proposed in this application should shed light on the epigenetic mechanisms and gene-environment interactions that result in vulnerability to depression.